Analysis of the Distribution of Urine Color and Its Relationship With Urine Dry Chemical Parameters Among College Students in Beijing, China – A Cross-Sectional Study - Liu, Jingnan; Zhang, Zijuan; Pang, Xiaohan; Cheng, Yaxing; Man, Da; He, Xinyi; Zhao, Huihui; Zhao, Ruizhen; Wang, Wei (Frontiers in Nutrition, 2021)
Objectives: To provide a new classification method by analyzing the relationship between the urine color (Ucol) distribution and urine dry chemical parameters based on image digital processing, and to assess the reliability of Ucol to evaluate the states of body hydration and health. Methods: A cross-sectional study among 525 college students, aged 17-23 years old (59 males, 466 females) was conducted. Urine samples were obtained during physical examination and 524 of them were considered valid, including 87 normal samples and 437 abnormal dry chemistry parameters samples. Urinalysis included both micro-and macro-levels in which the CIE L*a*b* values and routine urine chemical examination were performed through Digital Imaging Colorimetry and Urine Chemical Analyzer, respectively. Results: L* (53.49 vs 56.69) in abnormal urine dry chemistry group was lower than normal group while b* (37.39 vs 33.80) was greater. Ucol can be initially classified based on shade by grouping b*. Abnormal urine dry chemical parameter samples were distributed more in the dark color group. Urine dry chemical parameters were closely related to Ucol. Urine specific gravity (USG), protein, urobilinogen, bilirubin, occult blood, ketone body, pH and the number of abnormal dry chemical parameters were all correlated with Ucol CIE L*a*b*; according to stepwise regression analysis, it was determined that more than 50 % of the variation in the three color space values came from the urine dry chemical parameters, and the b* value was most affected by USG (standardized coefficient β= 0.734, p < 0.05). Based on ROC analysis, Ucol ≥ 4 provided moderate sensitivity and good specificity (AUC = 0.892) for the detection of USG ≥ 1.020. Conclusions: Our finding on Ucol analysis shows that grouping Ucol based on b* value is an objective, simple and practical method, at the same time suggests that digital imaging colorimetry for Ucol quantification is a potential method for evaluating body hydration and potentially health.